Model predictive control for efficient operation of district cooling generation
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Date
2023-04-21Author
Mohammadi, Adeleh
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Abstract
The market for District Cooling Systems (DCS) is increasing in Europe as well as other parts
of the world due to climate change and higher demand for thermal comfort in the buildings.
The DCS have come into attention for their role in the energy efficient operation of buildings
and districts. Many attempts have been made to operate the District Energy Systems (DES)
more efficiently; however, a change in the method of modelling, simulation and control can
bring further improvements in the energy performance of DES. The DCS has its challenges
including low temperature differentials at the generation level, and optimal operation of the
overall system which require specific modelling and control techniques to overcome.
In this thesis, the literature is critically reviewed to find out the role of modelling and simulation
with respect to DCS. As a result, the current shortcomings in modelling and control of DCS
are investigated. Then, an integrated modelling and simulation framework is developed for
energy efficient and optimal operation of DCS. The predictive control approaches have proved
to be effective in the control of DES in recent years. The Model Predictive Control (MPC)
algorithms are exploited in a virtual testbed to increase the energy efficiency of District Cooling
Generation Systems (DCGS). This thesis was performed as part of the EU H2020 INDIGO
(2016-2020) project; the testbed and data used in the implementation of this thesis are provided
through EU H2020 INDIGO (2016-2020). Furthermore, the MPC solution is analysed
mathematically to prove its performance. The virtual testbed for modelling and control of the
DCGS is tested on the Basurto hospital building in Spain as a part of EU H2020 INDIGO
(2016-2020) project; the results are compared to the current control setup in the DCGS of
Basurto to show the effectiveness of the MPC framework in energy efficiency of the DCGS.
The comparisons show a theoretical 30% decrease in energy use using the MPC
implementation of this thesis on each chiller in DCGS while the desired temperature is
achieved for thermal comfort.